Field of Endeavor
The present disclosure relates to a system for predicting abnormality occurrence, and more particularly, to a system for predicting abnormality occurrence using a PLC (Programmable Logic Controller) log data configured to analyze a data of abnormity occurrence among data collected from a PLC data log module and to predict generation of abnormality sign (indication) when a data of similar condition occurs.
Background
Although a factory system was conventionally operated by independent manipulation of machines and/or devices in automation facilities at a traditional industrial site, changes in the system are being required these days as modern industries become more complicated and diversified. That is, a device is required to complement the complicated and diversified operation, and therefore, a PLC (Programmable Logic Controller) system for directly controlling sites has been developed.
The PLC is largely controlled unmannedly, and when an abnormal operation is discovered, the abnormal operation can be ascertained by allowing the PLC to monitor a series of operations or to store a log data such as past history in order to take a post-facto arrangement. A conventional PLC data log module stores a relevant device value along with time when a condition set up by a user is satisfied. However, in case data is stored for a long time, the conventional PLC data log module disadvantageously consumes lots of time for analyzing a data amount when the data amount grows larger. Furthermore, the data stored in the data log module performs no function at all before information inside a memory card stored with the data is checked and analyzed by a user.
That is, the conventional PLC data log module functions to store relevant device value when a condition set up by a user is satisfied, and fails to provide data trends, variations and values related to correlation by analyzing the stored data. Hence, the conventional PLC data log module lacks the function of providing generation of abnormality sign (indication) to a user when there is generated the abnormality sign (indication).